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Learning Analytics of Clinical Anatomy e-Cases

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Abstract

Interactive online resources to support the learning of clinical anatomy are limited. While there is an assumption that such resources are useful, it is not known whether or not these resources support students learning. A new online problem-based supplementary learning resource named clinical anatomy e-cases was developed using Moodle and piloted on undergraduate medical students (n = 282). We examined users and usage analytics within the online learning management system. This chapter presents results of a study undertaken to explore students’ experiences in utilizing the e-cases in an informal learning environment. 80.85 % of the students accessed the resource with 14.5 % repetitions. We also report on a number of indicators that can be used to assess learning outcomes in nonformal learning environment. The construction of the e-cases ensured student interaction and engagement, even during weekends and after hours. Regular usage promoted increased scores within the environment and their formative examinations. The use of such simple, tailor made online clinical resources might promote student engagement and augment student learning outside classroom setting.

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Correspondence to Vivek Perumal .

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Perumal, V., Daniel, B., Butson, R. (2017). Learning Analytics of Clinical Anatomy e-Cases. In: Kei Daniel, B. (eds) Big Data and Learning Analytics in Higher Education. Springer, Cham. https://doi.org/10.1007/978-3-319-06520-5_15

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  • DOI: https://doi.org/10.1007/978-3-319-06520-5_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06519-9

  • Online ISBN: 978-3-319-06520-5

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